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Optimal Operation of Residential Battery Energy Storage Systems under COVID-19 Load Changes

Author

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  • Zahraa Hijazi

    (DTE Electric, Detroit, MI 48226, USA
    Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA)

  • Junho Hong

    (Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA)

Abstract

Over the past few years as COVID-19 was declared a worldwide pandemic that resulted in load changes and an increase in residential loads, utilities have faced increasing challenges in maintaining load balance. Because out-of-home activities were limited, daily residential electricity consumption increased by about 12–30% with variable peak hours. In addition, battery energy storage systems (BESSs) became more affordable, and thus higher storage system adoption rates were witnessed. This variation created uncertainties for electric grid operators. The objective of this research is to study the optimal operation of residential battery storage systems to maximize utility benefits. This is accomplished by formulating an objective function to minimize distribution and generation losses, generation fuel prices, market fuel prices, generation at peak time, and battery operation cost and to maximize battery capacity. A mixed-integer linear programming (MILP) method has been developed and implemented for these purposes. A residential utility circuit has been selected for a case study. The circuit includes 315 buses and 100 battery energy storage systems without the connection of other distributed energy resources (DERs), e.g., photovoltaic and wind. Assuming that the batteries are charging overnight, the results show that energy costs can be reduced by 10% and losses can decrease by 17% by optimally operating batteries to support increased load demand.

Suggested Citation

  • Zahraa Hijazi & Junho Hong, 2024. "Optimal Operation of Residential Battery Energy Storage Systems under COVID-19 Load Changes," Energies, MDPI, vol. 17(6), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1420-:d:1357600
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    References listed on IDEAS

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    1. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    2. Li, Longxi & Mu, Hailin & Li, Nan & Li, Miao, 2016. "Economic and environmental optimization for distributed energy resource systems coupled with district energy networks," Energy, Elsevier, vol. 109(C), pages 947-960.
    3. Jiang, Peng & Fan, Yee Van & Klemeš, Jiří Jaromír, 2021. "Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities," Applied Energy, Elsevier, vol. 285(C).
    4. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    5. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    6. Vahidinasab, Vahid, 2014. "Optimal distributed energy resources planning in a competitive electricity market: Multiobjective optimization and probabilistic design," Renewable Energy, Elsevier, vol. 66(C), pages 354-363.
    7. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2013. "Analytical strategies for renewable distributed generation integration considering energy loss minimization," Applied Energy, Elsevier, vol. 105(C), pages 75-85.
    8. Mishra, Partha Pratim & Latif, Aadil & Emmanuel, Michael & Shi, Ying & McKenna, Killian & Smith, Kandler & Nagarajan, Adarsh, 2020. "Analysis of degradation in residential battery energy storage systems for rate-based use-cases," Applied Energy, Elsevier, vol. 264(C).
    9. Nottrott, A. & Kleissl, J. & Washom, B., 2013. "Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems," Renewable Energy, Elsevier, vol. 55(C), pages 230-240.
    10. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
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